Journal Article

Evaluation of community health worker's performance at home-based newborn assessment supported by mHealth in rural Bangladesh

Rahman, Mahbubur, Sarker, Supta, Nasim, Mizanul Islam, Shoab, Abul Kasham, Darmstadt, Gary L., Billah, Sk Masum, Ashrafee, Sabina, Jahan, Farjana, Shahidullah, Mohammad, Parvez, Sarker Masud, Foote, Eric, El Arifeen, Shams, Hoque, Md. Mahbubul, Islam, Muhammad Shariful, Hasan, Rezaul

2022

Overview

Background In low to middle-income countries where home births are common and neonatal postnatal care is limited, community health worker (CHW) home visits can extend the capability of health systems to reach vulnerable newborns in the postnatal period. CHW assessment of newborn danger signs supported by mHealth have the potential to improve the quality of danger sign assessments and reduce CHW training requirements. We aim to estimate the validity (sensitivity, specificity, positive and negative predictive value) of CHW assessment of newborn infants aided by mHealth compared to physician assessment. Methods In this prospective study, ten CHWs received five days of theoretical and hands-on training on the physical assessment of newborns including ten danger signs. CHWs assessed 273 newborn infants for danger signs within 48 h of birth and then consecutively for three days. A physician repeated 20% ( n  = 148) of the assessments conducted by CHWs. Both CHWs and the physician evaluated newborns for ten danger signs and decided on referral. We used the physician’s danger sign identification and referral decision as the gold standard to validate CHWs’ identification of danger signs and referral decisions. Results The referrals made by the CHWs had high sensitivity (93.3%), specificity (96.2%), and almost perfect agreement (K = 0.80) with the referrals made by the physician. CHW identification of all the danger signs except hypothermia showed moderate to high sensitivity (66.7–100%) compared to physician assessments. All the danger signs assessments except hypothermia showed moderate to high positive predictive value (PPV) (50–100%) and excellent negative predictive value (NPV) (99–100%). Specificity was high (99–100%) for all ten danger signs. Conclusion CHW's identification of neonatal danger signs aided by mHealth showed moderate to high validity in comparison to physician assessments. mHealth platforms may reduce CHW training requirements and while maintaining quality CHW physical assessment performance extending the ability of health systems to provide neonatal postnatal care in low-resource communities. Trial registration clinicaltrials.gov NCT03933423 , January 05, 2019.

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Bangladesh / Birth weight / Breastfeeding & lactation / Case management / Community / Community health aides / Community Health Workers / Decision making / E-health / Evaluation / Gestational age / Global positioning systems / GPS / Home births / Households / Humans / Hypothermia / Infant / Infant mortality / Infant, Newborn / Infants (Newborn) / Internal Medicine / Intervention / Light therapy / Medical examination / Medical referrals / Medicine / Medicine & Public Health / Menstruation / Methods / mHealth / Mothers / Neonatal health / Neonatal jaundice / Newborn babies / Pediatric research / Pediatrics / Performance evaluation / Practice / Prenatal care / Prospective Studies / Rural health services / Signs / Technology application / Telemedicine / Womens health